{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8335317b",
   "metadata": {},
   "source": [
    "# Questão 3 - Clusterização com K-Means\n",
    "Considere os dados apresentados na tabela abaixo. Determine os centroides dos aglome-\n",
    "rados \"clusters\" presentes nos dados, fazendo uso do algoritmo da rede competitiva que\n",
    "corresponde ao algoritmo K-means. Para tanto considere os itens **(a)** - **(c)** referentes ao processo de inicialização.\n",
    "<center>\n",
    "\n",
    "Amostra   | $X_1$ | $X_2$ | $X_3$\n",
    ":--------:|:-------:|:-------:|:------:\n",
    "1         |-7.82  |-4.58  |-3.97\n",
    "2         |-6.68  |3.16   |2.71\n",
    "3         |4.36   |-2.19  |2.09\n",
    "4         |6.72   |0.88   |2.80\n",
    "5         |-8.64  |3.06   |3.50\n",
    "6         |-6.87  |0.57   |-5.45\n",
    "7         |4.47   |-2.62  |5.76\n",
    "8         |6.73   |-2.01  |4.18\n",
    "9         |-7.71  |2.34   |-6.33\n",
    "10        |-6.91  |-0.49  |-5.68\n",
    "11        |6.18   |2.81   |5.82\n",
    "12        |6.72   |-0.93  |-4.04\n",
    "13        |-6.25  |-0.26  |0.56\n",
    "14        |-6.94  |-1.22  |1.13\n",
    "15        |8.09   |0.20   |2.25\n",
    "16        |6.81   |0.17   |-4.15\n",
    "17        |-5.19  |4.24   |4.04\n",
    "18        |-6.38  |-1.74  |1.43\n",
    "19        |4.08   |1.30   |5.33\n",
    "20        |6.27   |0.93   |-2.78\n",
    "</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41296259",
   "metadata": {},
   "source": [
    "## Passando os dados para um Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6b8af78",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = [-7.82, -6.68, 4.36, 6.72, -8.64, -6.87, 4.47, 6.73, -7.71, -6.91, 6.18, 6.72, -6.25, -6.94, 8.09, 6.81, -5.19, -6.38, 4.08, 6.27]\n",
    "x2 = [-4.58, 3.16, -2.19, 0.88, 3.06, 0.57, -2.62, -2.01, 2.34, -0.49, 2.81, -0.93, -0.26, -1.22, 0.20, 0.17, 4.24, -1.74, 1.30, 0.93]\n",
    "x3 = [-3.97, 2.71, 2.09, 2.80, 3.50, -5.45, 5.76, 4.18, -6.33, -5.68, 5.82, -4.04, 0.56, 1.13, 2.25, -4.15, 4.04, 1.43, 5.33, -2.78]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a3dcff16",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# Create a DataFrame from the lists\n",
    "df = pd.DataFrame({'x1': x1, 'x2': x2, 'x3': x3})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37772e5c",
   "metadata": {},
   "source": [
    "## **a)** Considere que existam três clusters e a inicialização dos centros seja aleatória"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f9bddeb",
   "metadata": {},
   "source": [
    "### Distribuição dos Dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "11f43a5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plot the data\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(df[\"x1\"],df[\"x2\"],df[\"x3\"],s=40)\n",
    "plt.title('Data Distribution', pad=20, size=20)\n",
    "ax.set_xlabel('$X_1$', fontsize=16)\n",
    "ax.set_ylabel('$X_2$', fontsize=16)\n",
    "ax.set_zlabel('$X_3$', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4038a5f0",
   "metadata": {},
   "source": [
    "### Inicializando e Treinando Modelo K-Means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "46c82e59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(init=&#x27;random&#x27;, max_iter=1000, n_clusters=3, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KMeans</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.cluster.KMeans.html\">?<span>Documentation for KMeans</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>KMeans(init=&#x27;random&#x27;, max_iter=1000, n_clusters=3, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "KMeans(init='random', max_iter=1000, n_clusters=3, random_state=42)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "# instantiate the model\n",
    "kmeans = KMeans(init='random', n_clusters=3, random_state=42, max_iter=1000)\n",
    "# fit the model\n",
    "kmeans.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9151d5fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de iterações realizadas até a convergência: 3\n",
      "Centro 1: [-7.3275  6.043  -6.68  ]\n",
      "Centro 2: [-0.54       -0.146       1.20666667]\n",
      "Centro 3: [-5.3575      1.726       2.22833333]\n"
     ]
    }
   ],
   "source": [
    "# get number of interations performed until convergence\n",
    "print(f\"Número de iterações realizadas até a convergência: {kmeans.n_iter_}\")\n",
    "# get cluster centers\n",
    "print(f\"Centro 1: {kmeans.cluster_centers_[:, 0]}\\nCentro 2: {kmeans.cluster_centers_[:, 1]}\\nCentro 3: {kmeans.cluster_centers_[:, 2]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d03ce3f",
   "metadata": {},
   "source": [
    "### Plotando Resultados dos Centroides Encontrados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c1bf0527",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get the labels\n",
    "labels = kmeans.labels_\n",
    "\n",
    "# plot the data hilighting the centroids\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(x1, x2, x3, c=labels, s=40)\n",
    "ax.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], kmeans.cluster_centers_[:, 2], c='red', s=80, marker='*')\n",
    "plt.title('Data Distribution with the centroids', pad=10, size=12)\n",
    "ax.set_xlabel('$X_1$', fontsize=12)\n",
    "ax.set_ylabel('$X_2$', fontsize=12)\n",
    "ax.set_zlabel('$X_3$', fontsize=12, labelpad=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "963a7511",
   "metadata": {},
   "source": [
    "## **b)** Considere que existam três clusters e a inicialização dos centros seja dada por $m_1=(0,0,0)^t, m_2=(1,1,1)^t, m_3=(-1,0,2)^t$.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8533af78",
   "metadata": {},
   "source": [
    "### definindo a matriz de inicialização dos 3 centros conforme o especificado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "07e23ed6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1, -1],\n",
       "       [ 0,  1,  0],\n",
       "       [ 0,  1,  2]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "# inicialize the model with the centroids in m1, m2 and m3\n",
    "m1 = [[0],[0],[0]]\n",
    "m2 = [[1],[1],[1]]\n",
    "m3 = [[-1],[0],[2]]\n",
    "\n",
    "init = np.concatenate((m1, m2, m3), axis=1)\n",
    "init"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ea3ef1b",
   "metadata": {},
   "source": [
    "### Inicializando e Treinando Modelo K-Means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0e948146",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/efrainmpp/Documents/Mestrado/Neural-Network-PPGEEC2321/.venv/lib/python3.9/site-packages/sklearn/cluster/_kmeans.py:1404: RuntimeWarning: Explicit initial center position passed: performing only one init in KMeans instead of n_init=3.\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(init=array([[ 0,  1, -1],\n",
       "       [ 0,  1,  0],\n",
       "       [ 0,  1,  2]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KMeans</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.cluster.KMeans.html\">?<span>Documentation for KMeans</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>KMeans(init=array([[ 0,  1, -1],\n",
       "       [ 0,  1,  0],\n",
       "       [ 0,  1,  2]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "KMeans(init=array([[ 0,  1, -1],\n",
       "       [ 0,  1,  0],\n",
       "       [ 0,  1,  2]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# instantiate the model\n",
    "kmeans = KMeans(init=init, n_init=3, n_clusters=3, random_state=0, max_iter=1000)\n",
    "\n",
    "# fit the model\n",
    "kmeans.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "dceeb93e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de iterações realizadas até a convergência: 3\n",
      "Centro 1: [-0.28166667 -6.84285714  5.80428571]\n",
      "Centro 2: [ 0.43166667  0.38       -0.23285714]\n",
      "Centro 3: [-4.73833333  1.34285714  4.03285714]\n"
     ]
    }
   ],
   "source": [
    "# get number of interations performed until convergence\n",
    "print(f\"Número de iterações realizadas até a convergência: {kmeans.n_iter_}\")\n",
    "# get cluster centers\n",
    "print(f\"Centro 1: {kmeans.cluster_centers_[:, 0]}\\nCentro 2: {kmeans.cluster_centers_[:, 1]}\\nCentro 3: {kmeans.cluster_centers_[:, 2]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12537664",
   "metadata": {},
   "source": [
    "### Plotando Resultados dos Centroides Encontrados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "dd099132",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get the labels\n",
    "labels = kmeans.labels_\n",
    "\n",
    "# plot the data hilighting the centroids\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(x1, x2, x3, c=labels, s=40)\n",
    "ax.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], kmeans.cluster_centers_[:, 2], c='red', s=80, marker='*')\n",
    "plt.title('Data Distribution with the centroids', pad=10, size=12)\n",
    "ax.set_xlabel('$X_1$', fontsize=12)\n",
    "ax.set_ylabel('$X_2$', fontsize=12)\n",
    "ax.set_zlabel('$X_3$', fontsize=12, labelpad=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10e9c227",
   "metadata": {},
   "source": [
    "## **c)** Repita o item a considerando que os centros iniciais sejam $m_1=(-0.1,0,0.1)^t, m_2=(0,-0.1,0.1)^t, m_3=(-0.1,-0.1,0.1)^t$. Compare o resultado obtido com o item (a) e explique a razão das diferenças, incluindo o número de interações para alcançar a convergência."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dc9a0f5",
   "metadata": {},
   "source": [
    "### Definindo a matriz de inicialização dos 3 centros conforme o especificado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3c21ada5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.1,  0. , -0.1],\n",
       "       [ 0. , -0.1, -0.1],\n",
       "       [ 0.1,  0.1,  0.1]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inicialize the model with the centroids in m1, m2 and m3\n",
    "m1 = [[-0.1],[0],[0.1]]\n",
    "m2 = [[0],[-0.1],[0.1]]\n",
    "m3 = [[-0.1],[-0.1],[0.1]]\n",
    "\n",
    "init = np.concatenate((m1, m2, m3), axis=1)\n",
    "init"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ae260a7",
   "metadata": {},
   "source": [
    "### Inicializando e Treinando Modelo K-Means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "baf775b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/efrainmpp/Documents/Mestrado/Neural-Network-PPGEEC2321/.venv/lib/python3.9/site-packages/sklearn/cluster/_kmeans.py:1404: RuntimeWarning: Explicit initial center position passed: performing only one init in KMeans instead of n_init=3.\n",
      "  super()._check_params_vs_input(X, default_n_init=10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(init=array([[-0.1,  0. , -0.1],\n",
       "       [ 0. , -0.1, -0.1],\n",
       "       [ 0.1,  0.1,  0.1]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KMeans</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.cluster.KMeans.html\">?<span>Documentation for KMeans</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>KMeans(init=array([[-0.1,  0. , -0.1],\n",
       "       [ 0. , -0.1, -0.1],\n",
       "       [ 0.1,  0.1,  0.1]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "KMeans(init=array([[-0.1,  0. , -0.1],\n",
       "       [ 0. , -0.1, -0.1],\n",
       "       [ 0.1,  0.1,  0.1]]),\n",
       "       max_iter=1000, n_clusters=3, n_init=3, random_state=0)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# instantiate the model\n",
    "kmeans = KMeans(init=init, n_init=3, n_clusters=3, random_state=0, max_iter=1000)\n",
    "\n",
    "# fit the model\n",
    "kmeans.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bc6f5fb6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de iterações realizadas até a convergência: 3\n",
      "Centro 1: [-6.939       6.6         5.80428571]\n",
      "Centro 2: [ 0.508       0.05666667 -0.23285714]\n",
      "Centro 3: [-0.806      -3.65666667  4.03285714]\n"
     ]
    }
   ],
   "source": [
    "# get number of iterations\n",
    "print(f\"Número de iterações realizadas até a convergência: {kmeans.n_iter_}\")\n",
    "\n",
    "# get centroids\n",
    "print(f\"Centro 1: {kmeans.cluster_centers_[:, 0]}\\nCentro 2: {kmeans.cluster_centers_[:, 1]}\\nCentro 3: {kmeans.cluster_centers_[:, 2]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b3eaeaf",
   "metadata": {},
   "source": [
    "### Plotando Resultados dos Centroides Encontrados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f49fed06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get the labels\n",
    "labels = kmeans.labels_\n",
    "\n",
    "# plot the data hilighting the centroids\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(x1, x2, x3, c=labels, s=40)\n",
    "ax.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], kmeans.cluster_centers_[:, 2], c='red', s=80, marker='*')\n",
    "plt.title('Data Distribution with the centroids', pad=10, size=12)\n",
    "ax.set_xlabel('$X_1$', fontsize=12)\n",
    "ax.set_ylabel('$X_2$', fontsize=12)\n",
    "ax.set_zlabel('$X_3$', fontsize=12, labelpad=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81e574e2",
   "metadata": {},
   "source": [
    "# Conclusão\n",
    "Observa-se que o algoritmo K-means apresenta alta sensibilidade à escolha dos centróides iniciais. Na primeira execução, foi utilizado o método K-Means++ da biblioteca, que visa maximizar a distância entre os centróides iniciais, aumentando a probabilidade de encontrar uma solução globalmente ótima. Esse método seleciona o primeiro centróide aleatoriamente e os demais com base em uma distribuição proporcional à distância ao centróide mais próximo já escolhido.\n",
    "\n",
    "Nas execuções subsequentes, com inicializações explícitas dos centróides, foram observadas variações tanto nas posições finais dos centróides quanto no número de iterações necessárias para a convergência (2 iterações na primeira execução e 3 nas demais). Isso evidencia que a inicialização dos centróides pode impactar significativamente o resultado final do algoritmo, podendo levar a diferentes soluções locais e partições distintas dos dados. Portanto, a escolha adequada da estratégia de inicialização é fundamental para a obtenção de resultados mais robustos e consistentes em K-means."
   ]
  }
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